<p> The focus of this mixed-methods study was to identify waste reduction strategies that reduced the impact of California jails and prisons on the environment through waste diversion and reduction. This study also sought to identify barriers that hindered jail and prison personnel from developing such strategies, and pursued recommendations on how those barriers could be overcome.</p><p> Traditionally, California county jails and state prisons are resource intensive, overcrowded housing locations for about 200,000 adult men and women (Glaze &amp; Herberman, 2013). California jails and prisons operate 24 hours a day, seven days a week and utilize resources such as electricity, personnel, food, and other products. Accordingly, they generated significant waste (California Department of Resources and Recovery [CalRecycle], 2012). The prisoners alone generated about four pounds of waste per person each day, consistent with societal averages (CalRecycle, 2012; Corrections Corporation of America, 2007; Environmental Protection Agency [EPA], 2012a). Because of this, jails and prison must do more to reduce waste.</p><p> This study provided examples of organizations currently reducing waste through strategic initiatives and highlighted areas where jails and prisons could begin or further improve waste diversion practices. The study utilized archival data, a web-based survey, and interviews for data collection and analysis. The data from California jails and prisons were analyzed to identify strategies, barriers, and ways to eliminate or reduce barriers to waste reduction programs in California jails and prisons.</p><p> The findings conclude, California state-operated prisons and sheriff-operated county jails are using two primary strategies to divert waste from landfills. The number one strategy is recycling. The second strategy being used is waste prevention and material reuse. The barriers identified by California state-operated prisons and sheriff-operated county jails include finding vendors to collect certain materials as well as finding vendors to travel to remote locations. Other barriers include a lack of personnel and in some instances a lack of knowledge. Sheriff-operated jails and state-operated prisons in California identified waste management program support from leadership as a primary method to eliminate or reduce barriers to implementing a waste reduction program. Implications for action and future research are also discussed as part of this study.</p>

<p> How do firms adapt to the intensity of adverse conditions stemming from the natural environment (ecological adversity intensity)? In this dissertation, I develop several lines of inquiry in exploring this question. First, I seek to contribute to generally diverging perspectives on organizational adaptation, which view firms as either inherently constrained or capable of continuous adaptation to fit their environment. To do this, I examine the conditions under which firms are more likely to adapt to different levels of ecological adversity intensity. My findings from a 13-year longitudinal analysis of western U.S. ski resorts&rsquo; adaptation to temperature conditions indicate that firms facing moderate ecological adversity intensity appear more likely to engage in higher adaptation levels while those experiencing low and high ecological adversity intensity show a tendency for lower adaptation levels. That is, both diverging perspectives may predict part of firms&rsquo; adaptive responses to ecological adversity intensity. My findings also suggest firms may encounter limits to adaptation when facing increasing ecological adversity intensity. I also undertake a post hoc exploration of firm and institutional environment level factors that may moderate the relationship between ecological adversity intensity and firm adaptation. Second, I use an interdisciplinary approach that draws from resilience theory in socioecology to suggest that the existing conceptualization of organizational resilience could be expanded to include transformative change, which may allow firms to mitigate the operational impacts of reaching adaptation limits. Third, I also consider the resilience implications of the interdependency between firms and the broader ecosystems in which they operate. I conclude with potential avenues for future research in this area.</p><p>

The golf industry is an important sector of the recreation and tourism economy in Canada. In 2009, the Canadian golf industry generated an estimated total direct economic activity of CND$29.4 billion dollars and created over 300,000 jobs for Canadian residents. Within Canada, Ontario is the dominant province with regards to golf’s gross domestic product (GDP). In 2009, the 848 golf courses in Ontario generated $11.5 billion, which equates to 38.7% of Canada’s golf GDP (Strategic Networks Group, 2009). Due to the economic and employment benefits of the Ontario golf industry and its sizeable land use, it is important to fully understand the environmental impacts of golf courses. While concerns have been raised regarding water consumption by the Ontario golf industry, the golf industry in Ontario has never responded to these criticisms with actual water taking data to support their claims of environmental sustainability. Water withdrawals and water use efficiency among golf courses have yet to be quantified by the Province, the golf industry or its critics. This study uses daily water withdrawal data, self reported by 129 golf courses, to the Ministry of Environment (MOE) from 2007 to 2012. The water taking data is used to examine biophysical golf course characteristics that influence water use, to estimate annual water use by golf courses in Ontario, to identify the potential for water use reductions through best management practices (BMPs) and to explore how climate change may influence future golf course water use in Ontario. This study provides a first approximation of water use by irrigation for golf courses in Ontario. The analyses that examined the biophysical characteristics of golf courses indicated that soil type and golf course type influenced water use. During a dry season, golf courses composed of sand and silt dominated soils were found to require more water than they did during a climatically normal season. With regards to golf course type, premier private and private golf courses were found to use a greater quantity of water during both normal and dry seasons when compared to public and semi-private golf courses. The provincial water use analysis revealed that during a climatically normal season, 50.5 billion L of water is used to irrigate Ontario golf courses. Irrigation increased (58%) to 79.9 billion L during a season that was 1.2°C warmer and 29% dryer than normal. This finding indicates that under anticipated climate change by the 2050s, water use on golf courses in southern Ontario could increase by 151% current levels. The analysis for potential water savings for Ontario golf courses revealed that water use reductions of 35% are possible if golf courses adopt similar maintenance and irrigation practices to more efficient golf courses (80th percentile) in Ontario. Further research regarding maintenance practices on golf courses should be carried out to understand what best management practices result in water efficiency among courses. Also, due to the self-reporting nature of the water taking program with the MOE, it has been recommended that a more strict and automated monitoring system be implemented. Lastly, it is strongly believed that in order for the province wide water savings to be achieved, collaboration between the government and the golf industry will be needed. This study is the first approximate of water use for Ontario golf courses, however, more research is needed to examine the MOE’s water taking data in detail to better understand the determinants of water use among similar golf courses.

The continuous operation of civil and marine structures is essential for maintaining the flow of people and goods. However, structures are exposed to extreme or progressive events during their service time. The uncertainties associated with the occurrence and the magnitude of extreme events (e.g. flooding and scour) may change, leading to unprecedented loading conditions, while the progressive events (e.g. corrosion and fatigue) may jeopardize the structural capacity to resist loads. In order to maintain or improve the structural capacity, repair and maintenance actions need to be applied to structures. However, the determination of these actions may be challenging for decision makers due to (a) limited financial resources to be allocated for a group of structures, (b) uncertainties associated with current structure conditions and future loading conditions, and (c) various decision-making factors (e.g. reliability threshold, decision time, and risk attitude). In order to address these issues, the focus of the research in this dissertation is to enhance the development of management strategies with the application in (a) management of bridge networks under hydraulic events and climate changes, (b) service life extension of ships considering financial feasibility and decision-making factors, and (c) determination of reliability threshold in the decision-making process. The management of bridge networks involves the quantification of regional hazards imposed on the network, performance assessment of structures, and consequence evaluation of potential bridge failure. Regional hazards such as floods may be affected by the changes in the intensity of precipitation due to anticipated climate changes. These hazards may cause extensive damage to bridges, and failure may cause significant costs to bridge managers and result in inconvenience on the daily traffic commute. This research focuses on enhancing the assessment and management of bridges networks vulnerable to regional hydraulic events and climate changes. The integration of transportation network analysis, which reflects the redistribution of traffic flow in the event of bridge failure, is shown to be essential when determining the risk level of bridges. Furthermore, this work includes proposed methodologies for determining optimal management strategies that account for the connection between global climate predictions and regional hydrologic conditions. The crux of determining management strategies, especially for extending ship service lives, is to ensure an adequate safety margin within and beyond the design life. In addition to the loading effect and structural capacity, the safety margin of ships is related to the deterioration acting on the structure. During ship operation, in-service condition surveys are conducted on ship details to assess structural conditions and to inform maintenance actions. This research focuses on the integration of condition surveys of ship details, as well as the timing of conducting surveys, to improve the service life extension for ship structures. While decision makers strive to maintain the safe operation of ships, they should also identify the management strategy that can deliver the best return given the limited budget. This research, from the perspective of cost-effectiveness and profitability, proposes optimization frameworks to clarify the financially feasible life expectancy of different management strategies as well as identify the optimal duration of extended service life for different categories of commercial ships. The last focus of this research emanates from the reliability threshold when determining management strategies. In addition to facilitating decision-making on the management of civil and marine structures, the reliability threshold in terms of target reliability index has been extensively used in design guidelines to ensure adequate safety margin for structures. The level of safety is typically related to the failure mode and severity of failure consequences (e.g. number of potential fatalities). Driven by the emerging application of unmanned ships where there are fewer or no crew members on board, this research specifically focuses on the integration of different acceptance criteria for human safety into the determination of the target reliability index.

High mountain regions including the Andean region are very sensitive to climate change. Farmers in the central Andes of Peru are increasingly being exposed to the impacts of climate variability. This transdisciplinary research uses field laboratories, combining the farming system and the sustainable livelihood approaches, to carry out social, ecological, and financial assessments so as to identify sustainable and resilient livelihood strategies for small-scale Andean farmers. The first research step studies and characterizes farm household systems, influenced by their biophysical and socioeconomic contexts, for which two vulnerability indices were elaborated. Focused on the climate variability, the five livelihood assets and the three IPCC’s vulnerability components, these indices show the highly sensitive conditions of most communities with poor health conditions, access to infrastructure and public services. Farmers’ capacity of response is often limited by the low on-farm diversity and lack of organization. Thereafter, sustainable livelihood strategies were identified. These include on-farm intensification and non-farm labor intensification for lowland and better-access communities. In the middle-access and highland communities, where temporary migration is a common coping strategy, sustainable scenarios include an increment in diversification strategies through agrobiodiversity and a larger share of tree-based production systems. Furthermore, research step II explores local strategies to cope with agricultural droughts and evaluates, by means of natural resource assessment methods, agroforestry systems as an alternative to reduce their negative effects. Mainly affected by the increasing variation in precipitation events, farmers identify off-farm and on-farm diversification as adaptive strategies against agricultural droughts that reduce the weather dependence and covariance between livelihood activities. Among the introduction of more resistant crop and pasture varieties, the incorporation of trees in their system is desired because of their positive influence in soil moisture and crop yields. Soil moisture in agroforestry systems with eucalyptus trees is 10-20% higher than in agricultural systems during the beginning of the wet season. Differences in the soil moisture during the end of the dry season and in the potato yield are not evident between these systems, although an area without sowing reduced the agricultural output in 13-17% in agroforestry systems. Research step III seeks to maximize the efficiency of resource allocation in farm household systems by developing a linear programming optimization model. This financial assessment underpinned the need of additional off-farm activities for resource-scarcer farmers. In addition, under interest rates below 15% the model includes tree-based production systems as part of the optimal solution. However, with increasing interest rates, a higher share of land is used to cover household’s basic needs and fewer resources are available for capital accumulation activities such as forestry. Variations introduced in the model show that pasture systems are more sensitive to changes in the production outputs, whereas variation in farm worker wages and tree prices affected less the optimal solutions, making farming systems less sensitive to these market changes. Finally, the incorporation of tree-based systems have proved to be a sustainable and resilient livelihood strategy against climate variability available for particular farm household systems of the study area.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 - / Las zonas montañosas, incluyendo la región andina son muy sensibles al cambio climático. Los agricultores de los Andes centrales del Perú están cada vez más expuestos a los efectos de la variabilidad climática. Esta investigación transdisciplinaria utiliza laboratorios de campo (field laboratories), combinando los enfoques de sistemas agrícolas y de medios de vida sostenibles, para llevar a cabo evaluaciones sociales, ecológicas y financieras con el fin de identificar estrategias sostenibles y resilientes para los agricultores andinos de pequeña escala. La primera fase de la investigación caracteriza a los sistemas agrícolas familiares, influenciados por sus contextos biofísicos y socioeconómicos, para lo cual se elaboraron dos índices de vulnerabilidad centrados en la variabilidad del clima, los cinco activos de los medios de vida y los tres componentes de la vulnerabilidad del IPCC. Estos índices muestran las condiciones de alta sensibilidad de la mayoría de las comunidades, con malas condiciones de salud y poco acceso a la infraestructura y a los servicios públicos. La capacidad de respuesta de los agricultores es a menudo limitada por la baja diversidad en las actividades agrícolas y la falta de organización. Posteriormente se identificaron las estrategias de medios de vida sostenibles. Estas incluyen la intensificación en las actividades agrícolas y la intensificación del trabajo no agrícola en las comunidades de zonas bajas y con mejor acceso. En las comunidades con menor acceso y zonas altas la migración temporal es una estrategia de afrontamiento común. Los escenarios sostenibles en estas comunidades incluyen un incremento en las estrategias de diversificación p. ej. a través de un aumento de la biodiversidad agrícola y una mayor proporción de sistemas de producción asociados con árboles. Por otra parte, la segunda fase de la investigación explora las estrategias locales para hacer frente a las sequías agrícolas y evalúa, por medio de métodos de evaluación de recursos naturales, los sistemas agroforestales como alternativa para reducir sus efectos negativos. Afectados principalmente por el aumento en la variación de las precipitaciones, los pequeños agricultores identifican a la diversificación de actividades dentro y fuera de sus parcelas agrícolas como una estrategia de adaptación frente a las sequías agrícolas que reduce la dependencia climática y la covarianza entre las actividades de subsistencia. Dentro de la introducción de variedades de cultivos y pastos más resistentes, como parte de la solución, los agricultores desean la incorporación de árboles en su sistema debido a su influencia positiva en la humedad del suelo y en los rendimientos de los cultivos. La humedad del suelo en sistemas agroforestales con árboles de eucalipto es un 10-20% mayor que en los sistemas agrícolas durante el comienzo de la estación húmeda. Las diferencias en la humedad del suelo durante el final de la estación seca y en el rendimiento de los cultivos de papa no son evidentes entre estos dos sistemas. A pesar de esto, el espacio sin siembra dejado en los sistemas agroforestales redujo la producción agrícola en un 13-17%. La tercera fase de la investigación busca maximizar la eficiencia en la asignación de recursos en los sistemas agrícolas familiares mediante el desarrollo de un modelo de optimización de programación lineal. Esta evaluación financiera respalda la necesidad de actividades adicionales no-agrícolas para agricultores con recursos más escasos. Además, con tasas de interés por debajo del 15%, el modelo siempre incluye a los sistemas de producción forestales y/o agroforestales como parte de las soluciones óptimas. Sin embargo, con el aumento de las tasas de interés, una mayor proporción de tierra se utiliza para cubrir las necesidades básicas del hogar y menos recursos están disponibles para las actividades de acumulación de capital como la silvicultura. Las variaciones introducidas en el modelo muestran que los sistemas de pastoreo son más sensibles a los cambios en los condiciones de producción. Por otro lado, la variación en los salarios de los trabajadores agrícolas y en los precios de los árboles afectan en un menor grado las soluciones óptimas, proporcionando sistemas agrícolas menos sensibles a estos cambios en el mercado. Finalmente, la incorporación de árboles en los sistemas agrícolas ha demostrado ser una estrategia de vida sostenible y resiliente a la variabilidad climática disponible para determinados sistemas agrícolas familiares de la zona de estudio.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 - / Hochgebirgsregionen einschließlich der Andenregion sind gegenüber dem Klimawandel sehr empfindlich. Die in den zentralen Anden von Peru lebenden Bauern sind mehr und mehr den Auswirkungen durch Klimaschwankungen ausgesetzt. Diese transdisziplinäre Forschung nutzt Feldlabore, die das System der landwirtschaftlichen Bewirtschaftung und Ansätze zur nachhaltigen Lebensunterhaltssicherung kombinieren, um soziale, ökologische und ökonomische Erhebungen durchzuführen, so dass nachhaltige Livelihood-Strategien für die Kleinbauern in den Anden aufgezeigt werden können. Der erste Forschungsschritt untersucht und charakterisiert die bäuerlichen Haushaltssysteme, die durch ihre biophysikalischen und sozioökonomischen Kontexte beeinflusst sind. Hierfür wurden zwei Vulnerabilitätsindizes herausgearbeitet, die Klimavariabilität und die fünf Güter des Sustainable Livelihood-Konzepts im Fokus haben, sowie die drei Vulnerabilitätskomponenten des Intergovernmental Panel on Climate Change (IPCC). Diese Indizes decken die hochgradige Sensitivität für die meisten Gemeinden auf, aufgrund des schlechten Gesundheitszustandes sowie dem Mangel an Infrastruktur und öffentlichen Dienstleistungen. Die Fähigkeit der Bauern damit umzugehen, ist zumeist begrenzt durch eine geringe Diversität und fehlende Organisation auf den Farmen. Anschließend werden nachhaltige Livelihood-Strategien aufgezeigt. Diese umfassen die Intensivierung der Arbeit in der Landwirtschaft und der Arbeitskraft außerhalb der Landwirtschaft für Gemeinden im Flachland sowie besser erreichbare Gemeinden. In Hochlandgemeinden und Gemeinden die schwer zugänglich sind, ist temporäre Migration eine geläufige Bewältigungsstrategie. Nachhaltige Szenarien in diesen Gemeinden beinhalten eine höhere Anzahl an Diversifizierungsstrategien wie die Steigerung von Agro-Biodiversität und dem Anteil an baumbasierten Produktionssystemen. Forschungsschritt II untersucht lokale Strategien, um die landwirtschaftliche Dürre zu bewältigen und bewertet – mit Hilfe von Naturressourcenbewertungsverfahren – Agroforstsysteme als eine Alternative, um die negativen Auswirkungen der Trockenzeiten zu verringern. Beeinträchtigt durch zunehmende Niederschlagsschwankungen, identifizieren Bauern die Diversifizierung von landwirtschaftlichen und nicht-landwirtschaftlichen Aktivitäten als Anpassungsstrategie bei landwirtschaftliche Dürre, wodurch die Abhängigkeit vom Wetter und die Kovarianz zwischen den Aktivitäten für den Lebensunterhalt reduziert werden kann. Neben der Einführung resistenterer Kultur- und Weidepflanzen, ist die Einbeziehung von Bäumen in das System wünschenswert, aufgrund ihres positiven Einflusses auf die Bodenfeuchte und Erträge. Die Bodenfeuchte in agroforstwirtschaftlichen Systemen mit Eukalyptusbäumen ist während der beginnenden Feuchtperiode 20% höher als in landwirtschaftlichen Systemen. Die Unterschiede der Bodenfeuchte am Ende der Trockenzeit und bezüglich des Kartoffelertrags sind zwischen diesen Systemen nicht markant, obwohl eine Fläche, auf der keine Saat ausgebracht wurde, den landwirtschaftlichen Ertrag in Agroforstsystemen um 13 bis 17% mindert. Forschungsschritt III versucht die Effizienz der Ressourcenzuordnung in Farmhaushaltssystemen zu maximieren, indem ein Optimierungsmodell mit Hilfe der linearen Programmierung entwickelt wird. Diese ökonomische Erhebung unterstreicht die Notwendigkeit zusätzlicher nichtlandwirtschaftlicher Aktivitäten für ressourcenärmere Bauern. Bei Zinsraten unter 15% umfasst das Model baumbasierte Produktionssysteme als einen Teil der optimalen Lösung. Mit steigenden Zinsraten wird jedoch eine größere Bodenfläche dazu verwendet, um die Grundbedürfnisse der Haushalte zu decken und es stehen weniger Ressourcen für Aktivitäten zur Kapitalanhäufung wie Forstwirtschaft zur Verfügung. Die in das Modell involvierten Variationen zeigen, dass Weidesysteme sensibler auf Veränderungen des Produktionsausstoßes reagieren. Schwankungen bei den Löhnen der Farmer und Veränderungen der Baumpreise beeinträchtigen hingegen die optimalen Lösungen weniger. Dadurch sind die landwirtschaftlichen Systeme gegenüber Marktschwankungen weniger anfällig. Abschließend erweist sich, dass – für bestimmte Farmhaushaltssysteme im Untersuchungsgebiet – die Einbeziehung baumbasierter Systeme als nachhaltige und resiliente Livelihood-Strategie angesichts von Klimaschwankungen nützlich ist.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 - / Regiões altomontanas, incluindo os Andes são extremamente sensíveis aos impactos das mudanças climáticas. Pequenos agricultores da região central dos Andes Peruanos estão progressivamente sendo expostos aos impactos das variações climáticas. A presente investigação transdisciplinar utiliza “field laboratories”, combinando os enfoques de sistemas rurais e dos meios de subsistência sustentáveis, visando uma avaliação social, ecológica e financeira, com intuito de se identificar estratégias resilientes e sustentáveis para os pequenos agricultores Andinos. A primeira etapa do presente estudo investiga e caracteriza os sistemas rurais, influenciados por seus contextos biofísicos e socioeconômicos, para os quais foram elaborados dois índices de vulnerabilidade focados na variabilidade climática, nos recursos dos meios de vida (cinco capitais) e nos três componentes da vulnerabilidade do IPCC. Esses índices mostram as condições altamente sensíveis da maioria das comunidades, com más condições de saúde, acesso à infra-estrutura e serviços públicos. A capacidade de resposta dos pequenos agricultores é frequentemente limitada pela baixa diversificação de actividades na exploração agricola e falta de organização. Posteriormente, foram identificadas estratégias de subsitência sustentáveis. Estas incluem a intensificação tanto do trabalho rural, quanto do não-agrícola para as comunidades de terras baixas e mais acessíveis. Para as comunidades altomontanas e com menor acesso, a migração temporária é uma estratégia de enfrentamento comum. Cenários sustentáveis para essas comunidades incluem um incremento nas estratégias de diversificação p. ex. aumentando a agrobiodiversidade e a parcela dos sistemas de produção florestais. A segunda etapa da pesquisa explora estratégias locais para lidar com as secas agrícolas e investiga, por meio de métodos de avaliação de recursos naturais, sistemas agroflorestais como alternativa para reduzir os seus efeitos negativos. Afetado principalmente pelo aumento da variação da precipitação, os agricultores identificam a diversificação tanto no trabalho rural, quanto no não-agrícola, como estratégias adaptativas contra secas agrícolas que reduzam a dependência do clima e covariância entre atividades de subsitência. Entre a introdução de culturas e de pastagens de variedades mais resistentes, a incorporação de árvores em seu sistema é desejada por conta da sua influência positiva na umidade do solo e no rendimento das culturas. A umidade do solo em sistemas agroflorestais com árvores de eucalipto é de 10-20% maior do que em sistemas agrícolas durante o início da estação chuvosa. As diferenças na umidade do solo durante o final da estação seca e na produtividade da batata não são evidentes entre estes dois sistemas. Apesar disso, o espaço sem semeadura deixado em sistemas agroflorestais reduziu a produção agrícola em 13-17%. A terceira etapa da presente investigação visa maximizar a eficiência da alocação de recursos em sistemas agrícolas familiares por meio do desenvolvimento de um modelo de otimização de programação linear. Esta avaliação financeira sustenta a necessidade de atividades não-agrícolas adicionais para agricultores com recursos escassos. Ademais, sob taxas de juros abaixo de 15%, o modelo inclui sistemas de produção florestais como parte da solução ideal. Contudo, com o aumento das taxas de juros, uma parcela maior da propriedade é usada para garantir as necessidades básicas, e portanto, menos recursos do agregado familiar estão disponíveis para atividades de acumulação de capital, tais como a silvicultura. Variações introduzidas no modelo mostram que sistemas de pastagem são mais sensíveis a mudanças nas condições de produção. Ademais, variaçãoes nos salários dos trabalhadores agrícolas e nos preços de árvores afetam menos as soluções ótimas, tornando os sistemas agrícolas menos sensíveis a estas mudanças do mercado. Por fim, a incorporação de sistemas florestais provaram ser uma estratégia de subsistência sustentável e resiliente contra a variação climática para determinados sistemas de agricultura familiar da área de estudo.:1 Introduction - 1 - 1.1 Introduction and justification - 1 - 1.2 Objectives and thesis statements - 2 - 1.3 Outline - 3 - 1.4 Definition of terms - 5 - 1.4.1 Vulnerability - 5 - 1.4.2 Resilience - 7 - 1.4.3 Agroforestry systems - 8 - 1.4.4 Farming system approach - 9 - 1.4.5 Farm household system - 10 - 1.4.6 Sustainable livelihood approach - 10 - 2 Framework and study site - 14 - 2.1 Theoretical framework - 14 - 2.2 Methodological framework - 18 - 2.2.1 Field laboratories - 18 - 2.2.2 Methods - 19 - 2.2.3 Methodology applied in research step I: Vulnerability in Achamayo - 21 - 2.2.4 Methodology applied in research step II: Agroforestry systems and agricultural droughts - 29 - 2.2.5 Methodology applied in research step III: Modeling small farm production systems - 33 - 2.2.6 Selection of case studies - 34 - 2.3 Study area - 35 - 2.3.1 Soils and topography - 35 - 2.3.2 Weather - 37 - 2.3.3 Agro-ecological zones and vegetation - 38 - 2.3.4 Climate change - 40 - 2.3.5 Socioeconomic characteristics - 42 - 2.3.6 Population - 43 - 2.3.7 External determinants - 71 - 2.4 Case studies - 47 - 2.4.1 Lowland communities (L) - 49 - 2.4.2 Middle access communities (M) - 50 - 2.4.3 Highland communities (H) - 51 - 3 Vulnerability in Achamayo - 53 - 3.1 Results - 53 - 3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 - 3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 - 3.2 Discussion - 71 - 3.2.1 Climate variability and extreme events - 71 - 3.2.2 Human capital - 71 - 3.2.3 Social capital - 71 - 3.2.4 Natural capital - 71 - 3.2.5 Physical capital - 71 - 3.2.6 Financial capital - 71 - 3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 - 3.3 Conclusion - 92 - 4 Agroforestry systems and agricultural droughts - 95 - 4.1 Results - 96 - 4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 - 4.1.2 Agricultural droughts in the farm household systems - 97 - 4.1.3 Farming forestry systems and land-use decision-making - 102 - 4.1.4 Influence of trees in the soil moisture and yield - 104 - 4.2 Discussion - 110 - 4.2.1 Climate change and agricultural droughts - 110 - 4.2.2 Farm forestry systems and land-use decision-making - 115 - 4.2.3 Influence of trees in the soil moisture and yield - 117 - 4.3 Conclusion - 121 - 5 Modeling small farm production systems: optimization of resource allocation - 123 - 5.1 Methodology - 124 - 5.1.1 Optimization Model - 126 - 5.1.2 Plan of optimization - 128 - 5.1.3 Production systems - 131 - 5.1.4 Constraints - 134 - 5.2 Results - 138 - 5.2.1 Model - 138 - 5.2.2 Interest rates - 142 - 5.2.3 Sensitivity analyses - 146 - 5.3 Discussion - 151 - 5.3.1 Cash flows - 151 - 5.3.2 Model outcomes - 152 - 5.3.3 Interest rates - 155 - 5.3.4 Sensitivity analyses - 159 - 5.4 Conclusion - 169 - 6 Synthesis - 171 - 6.1 Lessons learned - 171 - 6.1.1 Research step I - 172 - 6.1.2 Research step II - 175 - 6.1.3 Research step III - 176 - 6.2 Conclusions & outlook - 179 - 6.2.1 General conclusions - 179 - 6.2.2 Outlook - 181 - References - 185 - Appendix - 199 -